ILRST 4740 Cornell: Data Mining and Machine Learning | StudySoup

PreparED Study Materials

ILRST 4740: Data Mining and Machine Learning

School: Cornell University

Number of Notes and Study Guides Available: 0

Videos

Uniform Data: Probabilities of Sample Means
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This video offers a comprehensive look into the discrete uniform population, analyzing a sample size of 54 selected with replacement. Through calculated steps, viewers learn how to determine probabilities for a sample mean within specified limits. Utilizing Z-scores and standard normal tables, the session illuminates statistical principles in real-world scenarios.

Sullivan's Algebra Scores: Frequency to Probabilities Analysis
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Explore Sullivan’s College Algebra homework score analysis, from frequency distribution construction to in-depth statistical calculations such as standard deviation. Discover histogram visualizations, mean and median interpretations, and probability estimations for various score thresholds. Utilize Excel functions for precise calculations.

ACT Score Bet: Who Owes the Pizza? A 7.6% Chance Explained
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Discover the friendly bet between Leona and Fred surrounding their ACT scores and who owes who a pizza. Using statistical principles like Z-scores and the normal distribution, we'll decipher the odds of one outperforming the other by 5 points.

Evaluating Expressions Using a Set of Scores
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Discover the methodology behind evaluating various mathematical expressions using a given set of scores. By interpreting and applying summation notation, learn how to compute the desired results from a set of numbers. Key conclusions showcase the step-by-step calculations and their significance.

Analyzing Teen Texting: Confidence Interval & Plausibility
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Discover how to calculate the 95% confidence interval for a population proportion using sample data. Through a practical example about texting habits among American teens, learn the implications of this statistical tool and how to assess plausibility.

Understanding Mutually Exclusive Events: Real-life Scenarios
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Explore the concept of mutually exclusive events in probability, using practical examples like rolling a die, selecting college students, and understanding political party registrations.

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